PCGETRF(l)
β¨ NAME β¨
PCGETRF β bestie, this one computes an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges. (And yeah, it's a LAPACK routine, version 1.5 energy. π)
π SYNOPSIS π
SUBROUTINE PCGETRF( M, N, A, IA, JA, DESCA, IPIV, INFO )
INTEGER IA, INFO, JA, M, N
INTEGER DESCA( * ), IPIV( * )
COMPLEX A( * )
π PURPOSE π
Okay so. PCGETRF computes an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges. That's the whole vibe.
The factorization has the form sub( A ) = P * L * U, where P is a permutation matrix, L is lower triangular with unit diagonal elements (lower trapezoidal if m > n), and U is upper triangular (upper trapezoidal if m < n). And where do L and U live afterwards? They're stored in sub( A ). Not me being efficient or anything. π
This is the right-looking Parallel Level 3 BLAS version of the algorithm. iykyk.
Notes
Each global data object is described by an associated description vector. This vector stores the information required to establish the mapping between an object element and its corresponding process and memory location.
Let A be a generic term for any 2D block cyclicly distributed array. Such a global array has an associated description vector DESCA. In the following comments, the character _ should be read as "of the global array".
Here's the notation lore, laid out for you π«Ά:
DTYPE_A(global) β stored inDESCA( DTYPE_ )β the descriptor type. In this case,DTYPE_A = 1.CTXT_A(global) β stored inDESCA( CTXT_ )β the BLACS context handle, indicating the BLACS process gridAis distributed over. The context itself is global, but the handle (the integer value) may vary.M_A(global) β stored inDESCA( M_ )β the number of rows in the global arrayA.N_A(global) β stored inDESCA( N_ )β the number of columns in the global arrayA.MB_A(global) β stored inDESCA( MB_ )β the blocking factor used to distribute the rows of the array.NB_A(global) β stored inDESCA( NB_ )β the blocking factor used to distribute the columns of the array.RSRC_A(global) β stored inDESCA( RSRC_ )β the process row over which the first row of the arrayAis distributed.CSRC_A(global) β stored inDESCA( CSRC_ )β the process column over which the first column of the arrayAis distributed.LLD_A(local) β stored inDESCA( LLD_ )β the leading dimension of the local array.LLD_A >= MAX(1,LOCr(M_A)).
Let K be the number of rows or columns of a distributed matrix, and assume that its process grid has dimension p x q.
LOCr( K ) denotes the number of elements of K that a process would receive if K were distributed over the p processes of its process column.
Similarly, LOCc( K ) denotes the number of elements of K that a process would receive if K were distributed over the q processes of its process row.
The values of LOCr() and LOCc() may be determined via a call to the ScaLAPACK tool function, NUMROC:
LOCr( M ) = NUMROC( M, MB_A, MYROW, RSRC_A, NPROW ),
LOCc( N ) = NUMROC( N, NB_A, MYCOL, CSRC_A, NPCOL ).
An upper bound for these quantities may be computed by:
LOCr( M ) <= ceil( ceil(M/MB_A)/NPROW )*MB_A
LOCc( N ) <= ceil( ceil(N/NB_A)/NPCOL )*NB_A
Heads up bestie: this routine requires square block decomposition ( MB_A = NB_A ). No exceptions, that's just the rule. π
π ARGUMENTS π
M(global input)INTEGERβ the number of rows to be operated on, i.e. the number of rows of the distributed submatrixsub( A ).M >= 0.N(global input)INTEGERβ the number of columns to be operated on, i.e. the number of columns of the distributed submatrixsub( A ).N >= 0.A(local input/local output)COMPLEXpointer into the local memory to an array of dimension(LLD_A, LOCc(JA+N-1)). On entry, this array contains the local pieces of the M-by-N distributed matrixsub( A )to be factored. On exit, this array contains the local pieces of the factorsLandUfrom the factorizationsub( A ) = P*L*U; the unit diagonal elements ofLare not stored. (Sneaky little omission, we love her for it. π)IA(global input)INTEGERβ the row index in the global arrayAindicating the first row ofsub( A ).JA(global input)INTEGERβ the column index in the global arrayAindicating the first column ofsub( A ).DESCA(global and local input)INTEGERarray of dimensionDLEN_. The array descriptor for the distributed matrixA.IPIV(local output)INTEGERarray, dimension( LOCr(M_A)+MB_A ). This array contains the pivoting information.IPIV(i)-> the global row local rowiwas swapped with. This array is tied to the distributed matrixA.INFO(global output)INTEGER:= 0: successful exit. π< 0: if thei-th argument is an array and thej-entry had an illegal value, thenINFO = -(i*100+j); if thei-th argument is a scalar and had an illegal value, thenINFO = -i.> 0: ifINFO = K,U(IA+K-1,JA+K-1)is exactly zero. The factorization has been completed, but the factorUis exactly singular, and division by zero will occur if it is used to solve a system of equations. π¨ This is the danger zone, bestie β do not pass go, do not solve that system.
And that's the whole page, fr fr. This was the LAPACK version 1.5 documentation, dated 12 May 1997 β vintage, iconic, still slaying. π¦β¨
π¦ where this page comes from
- ubuntu jammy: scalapack-doc 1.5-11
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms